REFER TO SEGMENT

Proper referencing of Segment when publishing scientific results is a prerequisite for using Segment. This is vital. We are dependent on proper citations in order to continue to release the software freely available for researchers.

Please send full bibliographic information (such as Pubmed link) of your final work when published or accepted for publication to support@medviso.com. Please see the list of researchers who has already remembered to give us credit by a proper citation.

A reference should encompass both the name Segment, and a suitable publication. When in doubt, please send an email to support@medviso.com or put reference [1] which is the generic reference for image analysis in Segment. This open-access paper describes Segment and its potential uses.

Examples of possible formulations for references

  • All image analysis was done using the freely available software Segment version 2.0 RXXXX (http://segment.heiberg.se) [1].
  • Global LV function was quantified using Segment v2.0 RXXXX (http://segment.heiberg.se) [1].
  • Infarct size was quantified using Segment v2.0 RXXXX (http://segment.heiberg.se) [4].

Note that referencing the software is manditory also for abstracts to scientific conferences. If shortage of space, at least reference the software as something like:
Images was analysed using the freely available software Segment (http://segment.heiberg.se).

In extreme shortage of space, such as conferences where the word limit is less than 350 words then reference may be omitted in the abstract text, but should be included in the oral presentation and / or poster.

References

LV segmentation

Using the new automatic LV segmentation in the software (version later than v2.0 R4265) should be referenced by [2]. Using the old semi automatic LV segmentation in the software (version earlier than v1.9 R4245) should be referenced by [3]. Using the software for manual segmentation of the LV should be referenced by [1].

[2] J. Tufvesson, E. Hedstrom, K. Steding-Ehrenborg, M. Carlsson, H. Arheden, and E. Heiberg, Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging, Biomed Res Int, 2015:970357.
[3] E. Heiberg, L. Wigström, M. Carlsson, A.F. Bolger, M. Karlsson, Time Resolved Three-dimensional Segmentation of the Left Ventricle, In proceedings of IEEE Computers In Cardiology 2005(32), pp. 599-602, Lyon, France, 2005.

Infarct quantification

The current algorithm for infarct quantification is EWA and should be referenced as [4]. The old weighted version should be referenced as [5]. Measurement of endocardial extent should be referenced to as [6]. Gray zone analysis should be referenced as gray zone analysis using weighted method using either [4] or [5] as reference. If the ROI based gray zone algorithm is used then the algorithm should be referred to as [7].

[4] H. Engblom, J. Tufvesson, R. Jablonowski, M. Carlsson, A. H. Aletras, P. Hoffmann, A. Jacquier, F. Kober, B. Metzler, D. Erlinge, D. Atar, H. Arheden, and E. Heiberg, A new automatic algorithm for quantification of myocardial infarction imaged by late gadolinium enhancement cardiovascular magnetic resonance: experimental validation and comparison to expert delineations in multi-center, multi-vendor patient data, J Cardiovasc Magn Reson 18(1) p 27, 2016.
[5] E. Heiberg, M. Ugander, H. Engblom, M. Götberg, G. K. Olivecrona, D. Erlinge, and H. Arheden, Automated quantification of myocardial infarction from MR images by accounting for partial volume effects: animal, phantom, and human study, Radiology 246(2) pp. 581-8, 2008.
[6] H. Engblom, M. B. Carlsson, E. Hedstrom, E. Heiberg, M. Ugander, G. S. Wagner, and H. Arheden, The endocardial extent of reperfused first-time myocardial infarction is more predictive of pathologic Q waves than is infarct transmurality: a magnetic resonance imaging study, Clin Physiol Funct Imaging 27(2) pp. 101-8, 2007.
[7] Wu KC, Gerstenblith G, Guallar E, Marine JE, Dalal D, Cheng A, Marbán E, Lima JAC, Tomaselli GF, Weiss RG. Combined cardiac MRI and C-reactive protein levels identify a cohort at low risk for defibrillator firings and death. Circ Cardiovasc Imaging 2012; 5:178-86. PMCID:PMC3330427